/*
 * Copyright (C) 2025-2025. Huawei Technologies Co., Ltd. All rights reserved.
 * Licensed to the Apache Software Foundation (ASF) under one or more
 * contributor license agreements.  See the NOTICE file distributed with
 * this work for additional information regarding copyright ownership.
 * The ASF licenses this file to You under the Apache License, Version 2.0
 * (the "License"); you may not use this file except in compliance with
 * the License.  You may obtain a copy of the License at
 *
 *    http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */

package org.apache.spark.sql.catalyst.optimizer

import org.apache.spark.sql.catalyst.expressions._
import org.apache.spark.sql.catalyst.rules.Rule
import org.apache.spark.sql.execution.SparkPlan
import org.apache.gluten.execution.{SortExecTransformer, WindowExecTransformer}
import org.apache.spark.sql.catalyst.expressions.{SortOrder, Ascending}

case class CombineWindowSort ()
  extends Rule[SparkPlan] {

  override def apply(plan: SparkPlan): SparkPlan = {
    plan.transformUp {
      case w @ WindowExecTransformer(_, _, _, child: SortExecTransformer) =>
        if (child.output.isEmpty) {
            w
        }
        child match {
          case SortExecTransformer(sortOrder, _, sortChild, _) =>
            if (Seq(w.partitionSpec.map(SortOrder(_, Ascending)) ++ w.orderSpec) == Seq(sortOrder)) {
              WindowExecTransformer(w.windowExpression, w.partitionSpec, w.orderSpec, sortChild)
            } else {
              w
            }
          case _ => w
        }
    }
  }
}